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Defining data-driven primary transcript annotations with primaryTranscriptAnnotation in R.
Anderson, Warren D; Duarte, Fabiana M; Civelek, Mete; Guertin, Michael J.
Afiliação
  • Anderson WD; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA.
  • Duarte FM; Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA.
  • Civelek M; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA.
  • Guertin MJ; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22903, USA.
Bioinformatics ; 36(9): 2926-2928, 2020 05 01.
Article em En | MEDLINE | ID: mdl-31917388
SUMMARY: Nascent transcript measurements derived from run-on sequencing experiments are critical for the investigation of transcriptional mechanisms and regulatory networks. However, conventional mRNA gene annotations significantly differ from the boundaries of primary transcripts. New primary transcript annotations are needed to accurately interpret run-on data. We developed the primaryTranscriptAnnotation R package to infer the transcriptional start and termination sites of primary transcripts from genomic run-on data. We then used these inferred coordinates to annotate transcriptional units identified de novo. This package provides the novel utility to integrate data-driven primary transcript annotations with transcriptional unit coordinates identified in an unbiased manner. Highlighting the importance of using accurate primary transcript coordinates, we demonstrate that this new methodology increases the detection of differentially expressed transcripts and provides more accurate quantification of RNA polymerase pause indices. AVAILABILITY AND IMPLEMENTATION: https://github.com/WarrenDavidAnderson/genomicsRpackage/tree/master/primaryTranscriptAnnotation. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma / Genômica Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Genoma / Genômica Idioma: En Ano de publicação: 2020 Tipo de documento: Article